中国连片特困区经济韧性测度及影响因素分析

doi:10.18306/dlkxjz.2020.06.004

地理科学进展 ›› 2020, Vol. 39 ›› Issue (6): 924-937.doi: 10.18306/dlkxjz.2020.06.004

• 专辑 | 贫困地域系统演化 • 上一篇下一篇

中国连片特困区经济韧性测度及影响因素分析

丁建军, 王璋^*(), 柳艳红, 余方薇

吉首大学商学院,湖南吉首 416000

收稿日期:2019-12-31 修回日期:2020-04-21 出版日期:2020-06-28 发布日期:2020-08-28
通讯作者: 王璋
作者简介:丁建军(1980— ),男,湖南衡东人,博士,教授,博士生导师,主要从事区域经济与产业经济研究。E-mail: latt514@163.com
基金资助:
国家自然科学基金项目(41761022);湖南省杰出青年科学基金项目(2020JJ2025);湖南省社科基金重点项目(18ZDB031);生态旅游湖南省重点实验室平台项目(STLV1815);吉首大学校级人文社科研究项目(19SKY88)

Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis

DING Jianjun, WANG Zhang^*(), LIU Yanhong, YU Fangwei

School of Business, Jishou University, Jishou 416000, Hunan, China

Received:2019-12-31 Revised:2020-04-21 Online:2020-06-28 Published:2020-08-28
Contact: WANG Zhang
Supported by:
National Natural Science Foundation of China(41761022);Science Fund for Distinguished Young Scholars of Hunan Province(2020JJ2025);Key Program of Social Science Foundation in Hunan Province(18ZDB031);Platform Program of Key Laboratory of Ecotourism in Hunan Province(STLV1815);Project of Jishou University(19SKY88)

摘要/Abstract

摘要：

巩固脱贫攻坚成效,提升抗风险与自我发展能力对连片特困区而言意义深远。经济韧性作为反映区域经济应对冲击时抵抗、恢复、调整及转型能力的指标,能够有效评估连片特困区的抗冲击能力和返贫风险。基于中国12个连片特困区的地市级数据,通过构建综合指标体系及核心评估变量对其经济韧性进行了测度与对比,并运用多种回归模型识别主要影响因素,结果发现:① 连片特困区经济韧性小于非连片特困区,二者虽均呈逐年递增趋势,但非连片特困区增速略快。进一步对指数分解后发现,连片特困区与非连片特困区经济韧性的差距主要来自于适应与调整能力的差异。② 罗霄山区、燕山—太行山区、大别山区经济韧性均值最高,而滇西边境山区、六盘山区、四省藏区最低,东西差异明显。③ 大部分片区经济韧性逐年递增,经济韧性越高的片区往往增速越快,但四省藏区、六盘山区、吕梁山区经济韧性出现下降趋势,其中,吕梁山区下降最明显。在对不同片区经济韧性分解后发现,不同片区间适应与调整能力差异最大,创新与转型能力差异最小。④ 地理区位、人均固定资产投资、外贸依存度、财政自给水平、地方财政教育经费支出、专利授权数等变量对连片特困区经济韧性存在显著影响。⑤扶贫政策有利于增强片区经济韧性,经济韧性较低的片区对扶贫政策的依赖程度更高,其中,四省藏区、六盘山区、滇西边境山区对扶贫政策依赖最为严重。

关键词: 连片特困区, 经济韧性, 影响因素, 扶贫政策

Abstract:

It is of great significance to consolidate the achievements of poverty alleviation and enhance development capacity and the ability to resist shocks in contiguous poverty-stricken areas. Economic resilience, as an indicator of the resistance, recovery, adjustment, and transformation ability of regional economic systems in response to shocks, can effectively reflect the ability to resist shocks and the risk of returning to poverty in contiguous poverty-stricken areas. Based on the data of 12 contiguous poverty-stricken areas in China, economic resilience was measured and compared by constructing a comprehensive index system and core evaluation variables, and a variety of regression models were used to identify the main influencing factors. The results show that: 1) The economic resilience of contiguous poverty-stricken areas is lower than non-contiguous poverty-stricken areas. In both types of areas economic resilience has been increasing year by year, but the growth rate of non-contiguous poverty-stricken areas is slightly faster. After decomposing the index, it was found that the difference in economic resilience between contiguous poverty-stricken areas and non-contiguous poverty-stricken areas is primarily due to the ability to adapt and adjust. 2) Luoxiao Mountains, Yanshan-Taihang Mountains, and Dabie Mountains have the highest mean values of economic resilience, while the border mountainous areas in western Yunnan Province, Liupan Mountains, and the Tibetan area of four provinces have the lowest mean values of economic resilience. 3) The economic resilience of most areas was increasing. The areas with higher economic resilience tend to grow faster, but the economic resilience of the Tibetan area of four provinces, Liupan Mountains, and Lvliang Mountains showed a downward trend. Among them, the decline in Lvliang Mountains is the most obvious. After decomposing the economic resilience of different regions, it was found that the differences in adaptation and adjustment capabilities were the largest in different regions, and the differences in innovation and transformation capabilities were the smallest. 4) Variables such as geographical location, assets investment per capita, dependence on international trade, the level of self-sufficiency in finance, expenditure on education, and the number of patents have significant effects on the economic resilience and its growth in poverty-stricken areas. 5) Poverty alleviation policy is conducive to enhancing economic resilience. Areas with low economic resilience are highly dependent on poverty alleviation policies, among which the Tibetan areas in four provinces, Liupan Mountains, and the border mountainous areas of western Yunnan are most heavily dependent on poverty alleviation policies.

Key words: poverty-stricken areas, economic resilience, influencing factors, poverty alleviation policy

丁建军, 王璋, 柳艳红, 余方薇. 中国连片特困区经济韧性测度及影响因素分析[J]. 地理科学进展, 2020, 39(6): 924-937.

DING Jianjun, WANG Zhang, LIU Yanhong, YU Fangwei. Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis[J]. PROGRESS IN GEOGRAPHY, 2020, 39(6): 924-937.

图/表 14

图1

图2

表1

表2

图3

表3

图4

图5

图6

图7

表4

一般性因素影响回归结果"

变量	模型1 resi	模型2 resi	模型3 cresi	模型4 cresi	模型5 Δresi	模型6 Δresi
xi	-0.0244^***		-1.6429^***		-0.0008
mir	-0.0001		-0.2708^**		-0.0073
czhl	-0.0002	0.0023^***	-0.0645^***	0.0213	-0.0003	-0.0056^**
rgdp	0.0007	-0.0020	0.7980^***	0.5019^***	-0.0177^***	-0.0303
rmrj	0.0583^***	0.0583^**	3.4218^***	-0.1823	0.0249	0.1184
rgdtz	0.0011	0.0040^***	0.3320^***	0.1483^*	0.0120^***	0.0228^***
cyjg	-0.0001	0.0001	-0.0022	0.0002	-0.0008^*	0.0001
wmyc	-0.0221^***	-0.0133^**	-0.5711^***	-0.2293	-0.0231^**	-0.0564
zjsp	0.1074^***	0.0576^***	4.3024^***	0.9860^**	0.1017^*	0.3449^***
rczzc	-0.0228^***	-0.0116^*	-1.2929^***	-0.8059^**	-0.0474^**	-0.0290
rjyzc	0.0648	0.0725^***	4.6769	1.9726	0.4165^*	0.9593^***
rrdzc	-0.1061^*	0.0619	-18.4249^***	-3.5960^**	0.0584	-0.0918
zlsq	0.2457^***	0.1477^***	11.6059^***	3.0311^***	0.0928	0.2068
$R 2$	0.8433	0.8569	0.7397	0.6020	0.2713	0.4690

表4

表5

稳健性检验"

变量	模型7 resi	模型8 resi	模型9 cresi	模型10 cresi	模型11 Δresi	模型12 Δresi
czhl	0.0018^***	0.0040	0.0223	0.0926	-0.0071^***	-0.0006
rgdp	-0.0020	-0.0102^**	0.3647^**	1.3239^***	-0.0314	-0.0716^***
rmrj	0.0265	0.1166^***	-0.5555	-0.0836	0.1039	-0.0884
rgdtz	0.0037^***	0.0098^***	0.1888^**	-0.0090	0.0239^***	0.0331^***
cyjg	-0.0001	0.0027^**	-0.0015	0.0557^**	-0.0001	0.0071^***
wmyc	-0.0097^***	-0.1027^***	-0.0602	-4.4370^***	-0.0414	-0.2376^**
zjsp	0.0578^***	0.0763^***	-0.0369	0.9271	0.4428^***	0.2123^***
rczzc	-0.0147^***	0.0171	-0.8738^**	-0.8309^*	-0.0515^**	0.0459
rjyzc	0.0960^***	0.1559^**	3.0686^**	0.0804	1.0948^***	1.3108^***
rrdzc	0.0783^**	0.1079	-3.2552^*	0.3534	-0.0632	0.8144
zlsq	0.1866^***	0.0926^***	4.0758^**	2.2375^***	1.4074^**	-0.0658
$R 2$	0.8660	0.9470	0.5611	0.8445	0.3880	0.5933

表5

表6

扶贫政策影响回归结果⑥"

因变量		模型15 resi		模型16 cresi		模型17 resi		模型18 cresi		模型19 resi		模型20 cresi		模型21 s_resi		模型22 s_cresi
fpzc		0.017^***		0.979^***		0.016^***		0.945^***		0.013		1.073^***
s_fpzc														0.203^***		0.253^***
controls		是		是		是		是		是		是		是		是
$R 2$		0.466		0.322		0.544		0.332		0.638		0.499		0.466		0.322
因变量	模型23 s_rntcz		模型24 s_rgdtz		模型25 s_rmrj		模型26 s_resi		模型27 s_cresi		模型28 s_resi		模型29 s_cresi		模型30 s_resi		模型31 s_cresi
s_fpzc	0.228^***		0.096^***		0.590^***		0.163^***		0.200^***		0.155^***		0.222^***		-0.037		0.122^***
s_rntcz							0.176^***		0.233^***
s_rgdtz											0.498^***		0.325^***
s_rmrj															0.407^***		0.223^***
controls	是		是		是		是		是		是		是		是		是
$R 2$	0.206		0.342		0.687		0.495		0.414		0.564		0.398		0.703		0.451

表6

图8

参考文献 22

[1]	孙久文, 张静, 李承璋, 等. 我国集中连片特困地区的战略判断与发展建议[J]. 管理世界, 2019,35(10):150-159, 185.
	[ Sun Jiuwen, Zhang Jing, Li Chengzhang, et al. Strategic judgments and development suggestions on the development of poverty-stricken areas in China. Management World, 2019,35(10):150-159, 185. ]
[2]	唐丽霞, 李小云, 左停. 社会排斥、脆弱性和可持续生计: 贫困的三种分析框架及比较[J]. 贵州社会科学, 2010(12):4-10.
	[ Tang Lixia, Li Xiaoyun, Zuo Ting. Social exclusion, vulnerability and sustainable livelihoods: Three analytical frameworks and comparisons for poverty. Guizhou Social Sciences, 2010(12):4-10. ]
[3]	陈艾, 李雪萍. 脆弱性—抗逆力: 连片特困地区的可持续生计分析[J]. 社会主义研究, 2015(2):92-99.
	[ Chen Ai, Li Xueping. Vulnerability-resilience: Analysis of sustainable livelihoods in poverty-stricken areas. Socialism Studies, 2015(2):92-99. ]
[4]	韩峥. 脆弱性与农村贫困[J]. 农业经济问题, 2004(10):8-12, 79.
	[ Han Zheng. Vulnerability and rural poverty. Problem of Agricultural Economy, 2004(10):8-12, 79. ]
[5]	Martin R. Regional economic resilience, hysteresis and recessionary shocks[J]. Journal of Economic Geography, 2012,12(1):1-32.
[6]	Briguglio L, Cordina G, Farrugia N, et al. Economic vulnerability and resilience: Concepts and measurements[J]. Oxford Development Studies, 2009,37(3):229-247.
[7]	Fingleton B, Garretsen H, Martin R. Recessionary shocks and regional employment: Evidence on the resilience of UK regions[J]. Journal of Regional Science, 2012,52(1):109-133.
[8]	Holm J R, Ostergaard C R. Regional employment growth, shocks and regional industrial resilience: A quantitative analysis of the Danish ICT sector[J]. Regional Studies, 2015,49(1):95-112.
[9]	Brakman S, Garretsen H, Marrewijk V. Regional resilience across Europe: On urbanisation and the initial impact of the great recession[J]. Cambridge Journal of Regions Economy and Society, 2015,8(2):309-312.
[10]	Evans R, Karecha J. Staying on top: Why is Munich so resilient and successful?[J]. European Planning Studies, 2014,22(6):1259-1279.
[11]	Sensier M, Bristow G, Healy A. Measuring regional economic resilience across Europe: Operationalizing a complex concept[J]. Spatial Economic Analysis, 2016,11(2):1-24.
[12]	陈梦远. 国际区域经济韧性研究进展: 基于演化论的理论分析框架介绍[J]. 地理科学进展, 2017,36(11):1435-1444.
	[ Cheng Mengyuan. An international literature review of regional economic resilience: Theories and practices based on the evolutionary perspective. Progress in Geography, 2017,36(11):1435-1444. ]
[13]	张岩, 戚巍, 魏玖长, 等. 经济发展方式转变与区域弹性构建: 基于DEA理论的评估方法研究[J]. 中国科技论坛, 2012(1):81-88.
	[ Zhang Yan, Qi Wei, Wei Jiuchang. Transformation of the economic development mode and regional resilience construction: Study on evaluation method based on DEA theory. Forum on Science and Technology in China, 2012(1):81-88. ]
[14]	齐昕, 张景帅, 徐维祥. 浙江省县域经济韧性发展评价研究[J]. 浙江社会科学, 2019(5):40-46, 156.
	[ Qi Xin, Zhang Jingshuai, Xu Weixiang. A study on the evaluation of the development of county economic resilience in Zhejiang Province. Zhejiang Social Sciences, 2019(5):40-46, 156. ]
[15]	贺灿飞, 夏昕鸣, 黎明. 中国出口贸易韧性空间差异性研究[J]. 地理科学进展, 2019,38(10):1558-1570.
	[ He Canfei, Xia Xinming, Li Ming. Research on the spatial differences of China's export trade resilience. Progress in Geography, 2019,38(10):1558-1570. ]
[16]	张明斗, 冯晓青. 中国城市韧性度综合评价[J]. 城市问题, 2018(10):27-36.
	[ Zhang Mingdou, Feng Xiaoqing. Comprehensive evaluation on Chinese cities' resilience. Urban Problems, 2018(10):27-36. ]
[17]	张明斗, 冯晓青. 长三角城市群内各城市的城市韧性与经济发展水平的协调性对比研究[J]. 城市发展研究, 2019,26(1):82-91.
	[ Zhang Mingdou, Feng Xiaoqing. A comparative study of urban resilience and economic development level of cities in Yangtze River Delta urban agglomeration. Urban Development Studies, 2019,26(1):82-91. ]
[18]	徐圆, 张林玲. 中国城市的经济韧性及由来: 产业结构多样化视角[J]. 财贸经济, 2019,40(7):110-126.
	[ Xu Yuan, Zhang Linling. The economic resilience of Chinese cities and its origin: From the perspective of diversification of industrial structure. Finance & Trade Economics, 2019,40(7):110-126. ]
[19]	郭将, 许泽庆. 产业相关多样性对区域经济韧性的影响: 地区创新水平的门槛效应[J]. 科技进步与对策, 2019,36(13):39-47.
	[ Guo Jiang, Xu Zeqing. Research on the influence of industrial related variety on regional economic resilience: Analysis of threshold effect based on regional innovation level. Science & Technology Progress and Policy, 2019,36(13):39-47. ]
[20]	王宏, 阎建忠, 李惠莲. 中国14个连片特困地区的森林转型及其解释[J]. 地理学报, 2018,73(7):1253-1267.
	[ Wang Hong, Yan Jianzhong, Li Huilian. Forest transition and its explanation in contiguous destitute areas of China. Acta Geographica Sinica, 2018,73(7):1253-1267. ]
[21]	孙久文, 孙翔宇. 区域经济韧性研究进展和在中国应用的探索[J]. 经济地理, 2017,37(10):1-9.
	[ Sun Jiuwen, Sun Xiangyu. Research progress of regional economic resilience and exploration of its application in China. Economic Geography, 2017,37(10):1-9. ]
[22]	人民日报理论宣传部. 狂风暴雨不能掀翻大海[N]. 人民日报, 2019-09-06(9)
	[ People's Daily Theoretical Publicity Department. The storm cannot overturn the sea. People's Daily, 2019-09-06(9).

一级指标	权重	二级指标	指标性质	指标解释、计算方法及量纲	权重
抵抗与恢复能力	0.2168	地区生产总值	+	反映地区经济发展水平、绝对数(亿元)	0.3363
		农村居民人均可支配收入	+	反映农村居民风险抵抗能力、绝对数(元)	0.1212
		城乡居民储蓄余额	+	反映整体居民风险抵抗能力、绝对数(亿元)	0.3329
		产业结构HHI	-	反映地区产业结构多样化水平	0.1050
		外贸依存度	-	反映地区外贸依赖程度、进出口总额/地区生产总值(%)	0.1046
适应与调整能力	0.5336	财政自给水平	+	地方财政收入/地方财政支出(%)	0.1732
		地方财政支出	+	反映地方政府资源调配能力、绝对数(亿元)	0.2346
		固定资产投资总额	+	反映地区投资规模大小、绝对数(亿元)	0.2687
		社会消费品零售总额	+	反映地区市场规模大小、绝对数(亿元)	0.3235
创新与转型能力	0.2496	城镇化率	+	地区城镇常住人口/地区常住总人口(%)	0.1554
		地方财政教育事业支出	+	反映地方政府教育投入水平、绝对数(亿元)	0.2016
		产业高级化	+	一产产值占比×1+二产产值占比×2+三产产值占比×3	0.1027
		科研产出水平	+	地区科技成果数量/地区生产总值(%)	0.2752
		科研投入力度	+	地区R&D经费支出/地区生产总值(%)	0.2651

变量分类	变量名称	变量符号	计算方法与量纲
因变量	综合指标法韧性指数	resi	指标体系测度结果
	核心变量法韧性指数	cresi	式(4)测度结果
	综合指标法韧性指数变化率	Δresi	据指标体系测度结果计算所得(%)
一般性因素分析(回归1)
地理区位	是否西部地区	xi	虚拟变量
地理区位	是否民族自治州	mir	虚拟变量
经济基础	常住人口城镇化率	czhl	城镇常住人口/常住人口总数(%)
	人均地区生产总值	rgdp	绝对数(万元)
	农村居民人均可支配收入	rmrj	绝对数(万元)
	人均固定资产投资	rgdtz	绝对数(万元)
经济结构	产业结构	cyjg	二三产业产值/地区生产总值(%)
经济结构	外贸结构	wmyc	地区进出口总额/地区生产总值(%)
政策支持	财政自给水平	zjsp	地方财政收入/地方财政支出(%)
政策支持	人均地方财政支出	rczzc	绝对数(万元)
科教水平	人均地方财政教育事业支出	rjyzc	绝对数(万元)
	人均R&D经费支出	rrdzc	绝对数(万元)
	专利授权数量	zlsq	绝对数(万件)
扶贫政策因素分析(回归2)
扶贫政策	扶贫政策力度	fpzc	贫困县比例×国家支持系数×省级支持系数×年度强度系数
中介变量	农村居民人均可支配收入	rmrj	绝对数(万元)
	人均固定资产投资	rgdtz	绝对数(万元)
	人均农业产值	rntcz	绝对数(万元)

名称	经济韧性均值		总增长率
名称	数值	排序	数值/%	排序
罗霄山区	0.2135	1	45.78	1
燕山—太行山区	0.2052	2	28.00	8
大别山区	0.1929	3	41.11	3
吕梁山区	0.1743	4	04.31	12
乌蒙山区	0.1707	5	42.36	2
武陵山区	0.1459	6	35.67	4
大兴安岭南麓山区	0.1431	7	20.44	10
滇桂黔石漠化区	0.1408	8	28.85	7
秦巴山区	0.1321	9	32.62	5
滇西边境山区	0.1201	10	31.14	6
六盘山区	0.1077	11	22.46	9
四省藏区	0.0891	12	13.73	11

中国连片特困区经济韧性测度及影响因素分析

Measurement of economic resilience of contiguous poverty-stricken areas in China and influencing factor analysis

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 14

参考文献 22

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	付占辉, 梅林, 郑茹敏, 王彤彤. 东北地区城市女性就业水平空间分异机制[J]. 地理科学进展, 2020, 39(8): 1308-1318.
[2]	程晗蓓, 邹游, 林赛南, 李志刚. 居住迁移对居民健康的影响研究进展述评[J]. 地理科学进展, 2020, 39(7): 1210-1223.
[3]	刘倩, 陈佳, 吴孔森, 杨新军. 秦巴山集中连片特困区农户多维贫困测度与影响机理分析——以商洛市为例[J]. 地理科学进展, 2020, 39(6): 996-1012.
[4]	胡小芳, 李小雅, 王天宇, 赵红敏, 杨铄, 邓磊, 李景旺. 民宿空间分布的集聚模式与影响因素研究——基于杭州、湖州、恩施的比较[J]. 地理科学进展, 2020, 39(10): 1698-1707.
[5]	杨奎,张宇,赵小风,文琦,钟太洋. 乡村土地利用结构效率时空特征及影响因素[J]. 地理科学进展, 2019, 38(9): 1393-1402.
[6]	陈秧分, 刘玉, 王国刚. 大都市乡村发展比较及其对乡村振兴战略的启示[J]. 地理科学进展, 2019, 38(9): 1403-1411.
[7]	戴旭俊, 刘爱利. 地方认同的内涵维度及影响因素研究进展[J]. 地理科学进展, 2019, 38(5): 662-674.
[8]	李雪铭, 刘贺, 田深圳, 宫一路. 东北三省城市人居活动网络结构及影响因素分析——基于百度贴吧分析[J]. 地理科学进展, 2019, 38(11): 1726-1734.
[9]	何萍, 崔梅艳, 李矜霄, 刘树华. 昆明市太阳辐射变化特征及影响因子分析[J]. 地理科学进展, 2019, 38(11): 1793-1801.
[10]	杨文越, 曹小曙. 多尺度交通出行碳排放影响因素研究进展[J]. 地理科学进展, 2019, 38(11): 1814-1828.
[11]	宋琼, 赵新正, 李同昇, 刘静玉. 多重城市网络空间结构及影响因素——基于有向多值关系视角[J]. 地理科学进展, 2018, 37(9): 1257-1267.
[12]	宋伟轩, 马雨竹, 陈艳如. 南京城区住宅售租价格时空分异与影响因素[J]. 地理科学进展, 2018, 37(9): 1268-1276.
[13]	王建顺, 林李月, 朱宇, 艾尼江·杰力力. 西部民族地区流动人口户籍迁移意愿及影响因素——以新疆为例[J]. 地理科学进展, 2018, 37(8): 1140-1149.
[14]	王圣云, 罗玉婷, 韩亚杰, 李晶. 中国人类福祉地区差距演变及其影响因素——基于人类发展指数(HDI)的分析[J]. 地理科学进展, 2018, 37(8): 1150-1158.
[15]	廖凯华, 吕立刚. 东南湿润区坡面土壤水文过程研究进展与展望[J]. 地理科学进展, 2018, 37(4): 476-484.